Establishment of a Prediction Model for the Residual Stress on the Surface Layer of Face Gears During Hot Rolling by Jin Yuanyuan, Xu Hongyu, Li Li, Zhang Fengshou, Wang Xiaoqiang, Zhang Guang

“…Taking the simulation results as data samples, the response surface method is used to establish the prediction model of residual compressive stress and compressive stress layer depth on the surface of hot rolling gear profiles, and the optimal process combination is obtained by taking the maximum peak value of residual compressive stress and the minimum depth of residual compressive stress layer as the optimization objective. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…Among the tested algorithms, including bagging, gradient boosting, and AdaBoost, the bagging model achieved the highest accuracy (R 2 = 0.975). …”
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Stock Price Predictions with LSTM-ARIMA Hybrid Model under Neutrosophic Treesoft sets with MCDM interaction by Florentin Smarandache, G. Dhanalakshmi, Dr. S. Sandhiya

“…Forecasting stock performance has proven to be a challenging endeavour due to its increasing need for investment and growth prospects. At the forefront of machine learning, deep learning models facilitate the straightforward and efficient exploration and identification of optimal stocks, the hybrid forecasting models (LSTM and ARIMA) are used in the prediction of stock increase. …”
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Evaluating the Performance of a Fake News Model on A Domain-Specific and Heterogeneous Dataset to Improve Detection by Georgina Obuandike, Emmy Danny Ajik, Faith Oluwatosin Echobu

“…This study aims to improve fake news detection methods in distinct domains through in-depth dataset analysis using a Convolutional Neural Network (CNN), the research-trained models using an optimized CNN model on publicly available datasets. …”
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Prediction of Vigor of Naturally Aged Seeds from Xishuangbanna Cucumber (<i>Cucumis sativus</i> L. var. <i>xishuangbannanesis</i>) Using Hyperspectral Imaging by Meng Zhang, Jiangping Song, Huixia Jia, Xiaohui Zhang, Wenlong Yang, Yang Wang, Haiping Wang

“…Feature selection algorithms such as UVE (Uninformative Variables Elimination), SPA (Successive Projections Algorithm), and CARS (Competitive Adaptive Reweighted Sampling) were utilized to identify optimal spectral bands. Combined with KNN (K-Nearest Neighbor) and LogitBoost algorithms, predictive models for seed viability were established. …”
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Artificial intelligence in food system: Innovative approach to minimizing food spoilage and food waste by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Keru Duan, Gu Pang, Phemelo Tamasiga, Samran Khalid, Zainab T. Al-Sharify, Chinenye Ugwa

“…Artificial Intelligence (AI) presents transformative potential to mitigate these losses by enhancing food spoilage predictions and optimizing supply chain management. This paper examines the deployment of AI technologies such as machine learning models, predictive analytics, and advanced algorithm in predicting food spoilage with high accuracy, thereby reducing food waste substantially. …”
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Synthesis and application of MgCuAl-layered triple hydroxide/carboxylated carbon nanotubes/bentonite nanocomposite for the effective removal of lead from contaminated water by Usman M. Ismail, Ahmed I. Ibrahim, Sagheer A. Onaizi, Muhammad S. Vohra

“…Additionally, the machine learning (ML) and the ANN based models for lead removal using LTH/CNT-COOH/Bent nano-composite yielded good predictions.…”
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Detection of Hepatitis C Virus Infection from Patient Sera in Cell Culture Using Semi-Automated Image Analysis by Noemi Schäfer, Paul Rothhaar, Christian Heuss, Christoph Neumann-Haefelin, Robert Thimme, Julia Dietz, Christoph Sarrazin, Paul Schnitzler, Uta Merle, Sofía Pérez-del-Pulgar, Vibor Laketa, Volker Lohmann

“…The analysis of wild-type (WT) isolates was enabled by the expression of SEC14L2 and by inhibitors targeting deleterious host factors. Here, we aimed to optimize cell culture models to allow infection with HCV from patient sera. …”
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Identifying subtypes of longitudinal motor symptom severity trajectories in early Parkinson’s disease patients by Xiaozhou Xu, Xiaozhou Xu, Shushan Zhang, Chuanying Xu, Wei Zhang, Hui Zhao, Hui Zhao, Yumeng Liu, Shilei Zhai, Jie Zu, Jie Zu, Zhining Li, Lishun Xiao, Lishun Xiao, Lishun Xiao

“…The mAUC, accuracy, and macro F1-score of multi-class SVM model were 0.8846, 0.7692, and 0.7778, respectively. …”
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Modeling and Simulation Analysis of Bionic Flapping-Wing Flight Attitude Control Based on L1 Adaptive by Lun Li, Fan Bai, Wencheng Wang, Xiaojin Wu, Yihua Dong

“…At the same time, the Monte Carlo-support vector machine method is used to optimize the boundary of the control parameters in the flight control to obtain the control parameters that can meet the control expectations, and the obtained parameters are classified and judged according to the stable level flight conditions. …”
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Current trends and prospects for the development of research in hydroabrasive cutting technology in mining and general engineering by A.М. Makhno

“…The analysis of the results revealed the main directions of development of waterjet cutting, including optimization of cutting parameters, improvement of the quality of machined surfaces, modeling of the processes of interaction of abrasive particles with the material, and automation of technological process control. …”
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Line balancing problem with multi-manned workstations and resource constraints: The case of electronics waste disassembly by Yin-Yann Chen, Pourya Pourhejazy, Tzu-Ning Liu

“…The transformed AND/OR graph is used for prioritizing disassembly tasks in the modeling process. The method is applied for optimizing a real-world case of laptop disassembly to showcase the usefulness of the proposed approach. …”
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Screening colorectal cancer associated autoantigens through multi-omics analysis and diagnostic performance evaluation of corresponding autoantibodies by Zan Qiu, Yifan Cheng, Haiyan Liu, Tiandong Li, Yinan Jiang, Yin Lu, Donglin Jiang, Xiaoyue Zhang, Xinwei Wang, Zirui Kang, Lei Peng, Keyan Wang, Liping Dai, Hua Ye, Peng Wang, Jianxiang Shi

“…The presence of tumor-associated autoantibodies (TAAbs) in serum was subsequently assessed using enzyme-linked immunosorbent assays (ELISA) in 300 CRC patients and 300 healthy controls. Ten machine learning algorithms were utilized to develop diagnostic models, with the optimal one selected and integrated into an R Shiny-based GUI to enhance usability and accessibility. …”
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An energy trade-off management strategy for hybrid ships based on event-triggered model predictive control by Diju Gao, Long Chen, Yide Wang

“…First, torque models of the internal combustion engine (ICE) and electric machine (EM) are developed using a data-driven approach, followed by the construction of fuel consumption and carbon emission models. …”
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Differential Diagnosis Model of Hypocellular Myelodysplastic Syndrome and Aplastic Anemia Based on the Medical Big Data Platform by Jianhui Wu, Lu Zhang, Sufeng Yin, Haidong Wang, Guoli Wang, Juxiang Yuan

“…Then, the logistic regression model, decision tree model, BP neural network model, and support vector machine (SVM) model of hypo-MDS and AA were established. …”
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Early Warning for the Construction Safety Risk of Bridge Projects Using a RS-SSA-LSSVM Model by Gang Li, Ruijiang Ran, Jun Fang, Hao Peng, Shengmin Wang

“…To solve the challenges faced by early warnings risk and the low early warning accuracy in bridge construction safety, this study proposed a new early-warning model for bridge construction safety risk. The proposed model integrates a rough set (RS), the sparrow search algorithm (SSA), and the least squares support vector machine (LSSVM). …”
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The analysis of learning investment effect for artificial intelligence English translation model based on deep neural network by Yan Zhang, Shuangshuang Lyu

“…In short, the FACT model holds high application value in multimodal machine translation and language learning. …”
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Identification and validation of diagnostic biomarkers and immune cell abundance characteristics in Staphylococcus aureus bloodstream infection by integrative bioinformatics analys... by Junhong Shi, Li Shen, Yanghua Xiao, Cailing Wan, Bingjie Wang, Peiyao Zhou, Jiao Zhang, Weihua Han, Rongrong Hu, Fangyou Yu, Hongxiu Wang

“…Gene expression dataset GSE33341 was optimized as the discovery dataset, which contained samples from human and mice. …”
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AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes by Ang Li, Yunxin Wang, Hongxu Chen

“…This study explores the innovative applications of Natural Language Processing (NLP) and Large Language Models (LLMs) in biomedical diagnostics, particularly for AI-driven arrhythmia detection, hypertrophic cardiomyopathy (HCM) in athletes, and personalized medicine. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…This data analysis framework combines multiple predictive modeling approaches to achieve optimal results.ResultsThe horizontal type of impaction has the lowest S/W ratio (0.9267), indicating the least available distal to 2nd molar space. …”
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